TY - CHAP
T1 - Introduction
AU - Chakraborty, Somsubhra
AU - Weindorf, David C.
AU - Dasgupta, Shubhadip
N1 - Publisher Copyright:
© 2025 Elsevier Inc. All rights reserved.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - This chapter introduces the importance of soil characterization, which involves describing and quantifying physical, chemical, biological, mineralogical, and morphological properties of soils. It emphasizes the evolution from traditional, labor-intensive soil testing methods to sensor-based soil characterization, which offers real-time, precise data, making it a key tool in precision agriculture, environmental stewardship, and land management. Various sensor technologies such as visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS), portable X-ray fluorescence spectrometry (PXRF), laser-induced breakdown spectroscopy (LIBS), and electromagnetic induction are discussed, highlighting their role in enhancing soil analysis. The chapter also underscores the integration of sensors with artificial intelligence (AI) and machine learning to improve decision-making processes in agriculture, with practical applications ranging from soil fertility evaluation to environmental monitoring.
AB - This chapter introduces the importance of soil characterization, which involves describing and quantifying physical, chemical, biological, mineralogical, and morphological properties of soils. It emphasizes the evolution from traditional, labor-intensive soil testing methods to sensor-based soil characterization, which offers real-time, precise data, making it a key tool in precision agriculture, environmental stewardship, and land management. Various sensor technologies such as visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS), portable X-ray fluorescence spectrometry (PXRF), laser-induced breakdown spectroscopy (LIBS), and electromagnetic induction are discussed, highlighting their role in enhancing soil analysis. The chapter also underscores the integration of sensors with artificial intelligence (AI) and machine learning to improve decision-making processes in agriculture, with practical applications ranging from soil fertility evaluation to environmental monitoring.
KW - Artificial intelligence
KW - Machine learning
KW - Precision agriculture
KW - Sensor technology
KW - Soil characterization
KW - Soil fertility
UR - http://www.scopus.com/inward/record.url?scp=105006866506&partnerID=8YFLogxK
U2 - 10.1016/B978-0-443-29879-0.00002-2
DO - 10.1016/B978-0-443-29879-0.00002-2
M3 - Chapter
AN - SCOPUS:105006866506
SN - 9780443298806
T3 - Unlocking the Secrets of Soil: Applying AI and Sensor Technologies for Sustainable Land Use
SP - 1
EP - 16
BT - Unlocking the Secrets of Soil
PB - Elsevier
ER -